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Distributed plug & play predictive control - Certified control and computation under changing network topologies

The control of a network of interacting dynamical systems is a central challenge for addressing a range of emerging application problems.
Utilizing the connectivity and interactions in the network by exploiting advances in communication and computation technologies offers the potential for pushing these systems to higher performance while increasing efficiency of operation, which will reduce system over-design and associated costs. However, safety requirements and high system complexity represent key limiting factors for leveraging these new opportunities.

This talk will present some of our recent work that brings high-performance control with hard guarantees on system safety to distributed systems, offering a scalable and modular approach that exploits interconnection effects and flexibly adjusts to network changes. A new framework for plug and play distributed predictive control will be introduced and we will discuss essential theoretical and practical aspects for certifying distributed decision-making based on an optimization-in-the-loop paradigm. We will show how the proposed scheme ensures stability and constraint satisfaction of the global system without recourse to any centralized coordination, while allowing the control systems to optimize for performance. An application example of grid-aware electric vehicle charging will demonstrate the capabilities of the proposed theory. Lastly, we will address the computational aspects of the framework and present new results for certifying optimization with limited-precision computation or communication.

Type of Seminar:
Control Seminar Series
Prof. Melanie Zeilinger
ETH Zürich
Nov 23, 2015   16:15

Contact Person:

Prof. Florian Döfler
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Biographical Sketch:
Melanie Zeilinger is an Assistant Professor at the Department of Mechanical and Process Engineering at ETH Zurich. From 2012 to 2015 she was a Postdoctoral Researcher and Marie Curie fellow in a joint program with the University of California at Berkeley and the Max Planck Institute for Intelligent Systems in Tuebingen, Germany. From 2011-2012 she was a postdoctoral fellow at the École Polytechnique Fédérale de Lausanne (EPFL) in Switzerland. She received the Ph.D. degree in Electrical Engineering with honors from ETH Zurich in 2011, and the diploma in Engineering Cybernetics from the University of Stuttgart in Germany in 2006. Her research interests are centered around real-time and distributed control and optimization, as well as safe learning-based control, with applications to energy distribution and management systems and human-in-the-loop control.